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This conceptual article presents a schematic for use with extended cybernetic recursion in living systems and applies it to the issue of hyper vigilance as a demonstration of its utility.

The test-operate-test-exit (TOTE) schematic of Miller et al. (1960) is critically evaluated along with other schematics, including those of ordered cybernetics, and a new schematic is proposed, a recursive test-operate-test (rTOT), which emphasizes teleological purpose and hierarchical structure. The background psychophysiology of trauma is reviewed and then rTOT is applied to hyper vigilance, a cardinal component of post-traumatic stress disorder (PTSD).

Once the schematic was developed, it was applied to the behavior of hyper vigilance. Other applications are suggested.

As demonstrated, the rTOT schematic has potentially wide application because of its pragmatic and detailed structure.

The rTOT requires careful consideration of teleological purposes for its application and is simple enough, but also complex enough, for relevant utilization. Its compact nature and adjustable hierarchy scope are good mini-max complexity solutions for cybernetic, information modeling schematics.

The revealed teleological purpose of the trauma adaptation of hyper vigilance presents significant alternative formulation options for prevention and intervention.

While the rTOT schematic is derived from previous schematics, it is original in its emphasis on information processing, the teleological aspects of extended recursion and on the provision of a hierarchical structure for those recursions. It is considerably more compact than other schematics associated with the ordered cybernetics literature. The explication of the adaptation model for post-trauma consequences is significantly enhanced by the rTOT application.

This paper aims to propose the mechanism of cross-network effect embedded, which can help cross-border e-commerce (CBEC) platforms strengthen cooperative relationships with sellers more equitably and effectively by using the network structural characteristics of the platforms themselves.

A two-stage evolutionary game model has been used to confirm the influence factors. The mathematical derivation of evolutionary game analysis is combined with the simulation method to examine the role of cross-network effect in cooperation. The evolutionary game model based on the cross-network effect is proposed to achieve better adaptability to the study of cooperation strategy from the two-sided market perspective.

The evolutionary game model captures the interactions of cross-network effect and the influence factors from a dynamic perspective. The cross-network effect has a certain substitution on the revenue-sharing rate of SMEs. CBEC platforms can enhance the connection between consumers and the website by improving the level of construction, which is a good way to attract sellers more cost-effectively and efficiently.

This study provides a new method for the validation of the cross-network effect, especially when data collection is difficult. But this method is only a numerical simulation. So the conclusions still need to be further tested empirically. Besides, researchers are advised to explore the relationship between the added user scale and the cross-network effect in some specificCBEC platforms.

This study provides a new method for the validation of the cross-network effect, especially when data collection is difficult. But this method is only a numerical simulation. So the conclusions still need to be further tested empirically. Besides, researchers are advised to explore the relationship between the added user scale and the cross-network effect in some specific CBEC platforms.

Investigations that study cooperation strategy from the cross-network effect perspective in CBEC are limited. The research figured out which influence factors are affected by the cross-network effect in cooperation. A two-stage evolutionary game model was proposed to explain the interaction of the factors. The evolutionary game analysis with a simulation method was combined to highlight the role of cross-network effect on cooperation strategy to give a deeper investigation into the sustainable cooperation ofCBEC.

Prior research on relations between mental health and pain has focused on negative mental health aspects (e.g. depression), while the literature is scarce in terms of positive aspects, such as mental well-being. This study aims to investigate prospective associations of mental well-being at baseline with pain and functional impairment due to pain in the following year.

Data stem from a Danish nationally representative survey of 5,000 adults (aged 15+) conducted in 2019 and 2020, which was linked to register data. The Short Warwick–Edinburgh Mental Well-being Scale was used to assess mental well-being, both continuously (range 7–35) and categorically (low, moderate, high). Logistic regressions were conducted to assess associations between mental well-being in 2019 and pain and functional impairment due to pain (among those reporting any pain) in 2020.

In the fully adjusted models, each point increase in mental well-being was inversely associated with pain (OR = 0.97, 95%CI 0.95–0.99) and functional impairment due to pain (OR = 0.96, 95%CI 0.94–0.99). As compared to low mental well-being, moderate mental well-being was associated with an OR of 0.76 (95%CI 0.58–0.99) for pain and an OR of 0.63 (95%CI 0.46–0.87) of functional impairment due to pain, while high mental well-being was associated with an OR of 0.56 (95%CI 0.40–0.77) for pain and an OR of 0.53 (95%CI 0.34–0.79) for functional impairment due to pain.

Higher mental well-being levels may be protective against pain and functional impairment due to pain. Wider mental health promotion may be considered to prevent pain and associated functional impairments in the general population.

The aim of this study is to analyze the influence mechanism of real estate enterprises' status on debt default risk and explore the heterogeneity effect of the characteristics of enterprises.

Against the background of the “three red lines” regulation of the financing of real estate enterprises and the COVID-19 pandemic, the authors select 123 real estate enterprises listed on China's Shanghai and Shenzhen A-shares markets from the first quarter of 2021 to the second quarter of 2022 as a research sample. The social network analysis method and Z-score financial risk early warning model are used to measure real estate enterprises' status and debt default risk. The authors construct a panel regression model to analyze how the status of real estate enterprises influences their debt default risk.

The results show that the status of real estate enterprises negatively and significantly affects their debt default risk. Economic policy uncertainty and financing constraints play negative moderating and mediating roles, respectively. Further research has found that the effect of real estate enterprises' status on debt default risk is characterized by heterogeneity in equity characteristics, i.e. it is significant in the sample of nonstate-owned enterprises but not in the sample of state-owned enterprises.

It is helpful for real estate enterprises to attach importance to the value of social networks, and the authors provide policy suggestions for real estate enterprises to constantly improve their risk management systems.

Using economic policy uncertainty as the moderating variable and financing constraints as the mediating variable, the authors analyze how the status of real estate enterprises influences debt default risk, which contributes to a better understanding of the formation of the debt default risk of real estate enterprises.

The first purpose is to assess the quality of containerized multimodal export and the second is to develop and demonstrate the design of a service network with quality approach.

The article used the structural equation model to develop a model to measure the quality of multimodal transportation for containerized exports and finalized the model with an alternative approach. The evolutionary algorithm had been used to design a service network based on quality.

Provided factors affecting quality of multimodal transportation and reverse to one hypothesis, the construct variation in cost, time shape and quantity did not affect the quality of multimodal transportation for containerized exports. The model without variation construct was finalized by exploring causality.

This research had scope till container loading onto the vessel and assessed the quality for containerized cargo only, and second research purpose is limited by assumed values of fitness function and the limited number of nodes, in service network design demonstration.

This research provided a tool to measure the quality of multimodal transportation for containerized exports and demonstrated the field application of the model developed in service network design. This approach included all factors applicable across the container movement. The integrated approach of the article provided an organized method to design a service network for containerized exports.

This work provided the tool to assess the quality of multimodal transportation for containerized exports and developed an approach to design a service network of multimodal transportation based on quality. This approach has considered the factors of multimodal transportation comprehensively in contrast to the optimization approaches based on operation research techniques.

This paper aims to introduce a new fault protection scheme for microgrid DC networks with ring buses.

It is well recognized that the protection scheme in a DC ring bus microgrid becomes very complicated due to the bidirectional power flow. To provide reliable protection, the differential current signal is decomposed into several basic modes using adaptive variational mode decomposition (VMD). In this method, the mode number and the penalty factor are chosen optimally by using arithmetic optimization algorithm, yielding satisfactory decomposition results than the conventional VMD. Weighted Kurtosis index is used as the measurement index to select the sensitive mode, which is used to evaluate the discrete Teager energy (DTE) that indicates the occurrence of DC faults. For localizing cable faults, the current signals from the two ends are used on a sample-to-sample basis to formulate the state space matrix, which is solved by using generalized least squares approach. The proposed protection method is validated in MATLAB/SIMULINK by considering various test cases.

DTE is used to detect pole-pole and pole-ground fault and other disturbances such as high-impedance faults and series arc faults with a reduced detection time (10 ms) compared to some existing techniques.

Verification of this method is performed considering various test cases in MATLAB/SIMULINK platform yielding fast detection timings and accurate fault location.

This paper aims to study whether the adoption of an entry mode that fits the social trust level contributes to the improvement of foreign subsidiary performance.

The authors used the Probit model, linear regression, strategic fit approach and instrumental variable regression. The sample was made up of 11,095 observations of Chinese multinational enterprises' foreign subsidiaries in 54 countries from 2005 to 2020.

The results suggest that a host country with a high level of social trust results in fewer difficulties for enterprises in gaining legitimacy, thus foreign subsidiaries are more likely to select the wholly owned entry mode. The results also show that the effect is contingent on the formal institutions of host countries. The results of the mechanism test suggest that social trust influences subsidiaries' entry mode choice by reducing information asymmetry, costs and uncertainty risks. This study further finds that selecting a fit entry mode based on social trust level substantially increases foreign subsidiary performance and this effect is more significant when multinational enterprises (MNEs) are state-owned enterprises (SOEs).

The main limitation of this paper is its only focus on foreign subsidiaries of Chinese MNEs, which may limit the generalizability of research findings.

This paper responds to the call for conducting more research on informal institutions. Findings highlight the critical role of informal institutions in helping foreign subsidiaries in gaining legitimacy in host countries and the essentialness of selecting a fit entry mode based on the informal institutions of host countries for the development of foreign subsidiaries.

The determination of mode-I fracture toughness of brittle structural materials by means of the notched Brazilian disc configuration is studied. Advantage is taken of a recently introduced analytical solution and, also, of data provided by an experimental protocol with notched marble specimens under diametral compression using the loading device suggested by International Society for Rock Mechanics (ISRM) and also the three-dimensional digital image correlation (3D-DIC) technique.

The analytical solution highlighted the role of geometrical factors, like, for example, the width of the notch, which are usually disregarded. The data of the experimental protocol were comparatively considered with those concerning the response of the specific material under uniaxial tensile load.

This combined study provided interesting data concerning some open issues, as it is the exact crack initiation point and the level of the critical load causing crack initiation. It was definitely indicated that the crack initiation point is not a priori known (even for notched specimens) and, also, that the maximum recorded load does not correspond by default to the critical load responsible for the onset of catastrophic macroscopic fracture.

It was suggested that the load considered critical one for the determination of mode-I fracture toughness K_IC is erroneous. At a load equal to about 70% of the maximum one, a process zone is formed (zone of non-reversible phenomena) around the notch's crown, designating termination of the validity of any linear elastic solution used to determine the normalized stress intensity factors (SIFs). Moreover, at a load level equal to about 95% of the macroscopically observed fracture load, crack propagation has already begun. Therefore, the experimental procedure must be monitored with additional equipment, providing an overview of the displacement field developed during loading.

This paper aims to develop a dynamic civil facility degradation prediction model to forecast the reliability performance tendency and remaining useful life under imperfect maintenance based on the inspection records and the maintenance actions.

A real-time hidden Markov chain (HMM) model is proposed in this paper to predict the reliability performance tendency and remaining useful life under imperfect maintenance based on rare failure events. The model assumes a Poisson arrival pattern for facility failure events occurrence. HMM is further adopted to establish the transmission probabilities among stages. Finally, the simulation inference is conducted using Particle filter (PF) to estimate the most probable model parameters. Water seals at the spillway hydraulic gate in a Taiwan's reservoir are used to examine the appropriateness of the approach.

The results of defect probabilities tendency from the real-time HMM model are highly consistent with the real defect trend pattern of civil facilities. The proposed facility degradation prediction model can provide the maintenance division with early warning of potential failure to establish a proper proactive maintenance plan, even under the condition of rare defects.

This model is a new method of civil facility degradation prediction under imperfect maintenance, even with rare failure events. It overcomes several limitations of classical failure pattern prediction approaches and can reliably simulate the occurrence of rare defects under imperfect maintenance and the effect of inspection reliability caused by human error. Based on the degradation trend pattern prediction, effective maintenance management plans can be practically implemented to minimize the frequency of the occurrence and the consequence of civil facility failures.

For privacy protection, federated learning based on data separation allows machine learning models to be trained on remote devices or in isolated data devices. However, due to the limited resources such as bandwidth and power of local devices, communication in federated learning can be much slower than in local computing. This study aims to improve communication efficiency by reducing the number of communication rounds and the size of information transmitted in each round.

This paper allows each user node to perform multiple local trainings, then upload the local model parameters to a central server. The central server updates the global model parameters by weighted averaging the parameter information. Based on this aggregation, user nodes first cluster the parameter information to be uploaded and then replace each value with the mean value of its cluster. Considering the asymmetry of the federated learning framework, adaptively select the optimal number of clusters required to compress the model information.

While maintaining the loss convergence rate similar to that of federated averaging, the test accuracy did not decrease significantly.

By compressing uplink traffic, the work can improve communication efficiency on dynamic networks with limited resources.